Tools and utilities to catalogue and evaluate observation files.
Some of the observation inventory utils functionality relies on intel compilers, the nceplibs-bufr repo managed by EMC, and the UFS-RNR anaconda python module. As such, these tools/modules must also be installed.
- Clone the observation-inventory-utils repo.
$ git clone https://github.com/noaa-psd/observation-inventory-utils.git-
Install or setup the UFS-RNR anaconda3 python environment. If the UFS-RNR anaconda python environment is not already available, install it now using the instructions found in the UFS-RNR-stack repo. An example of the actual installation script can be found at scripts/build.UFS-RNR-stack.RDHPCS-Hera.anaconda3.sh. If you are installing this anaconda module at a different location than what is configured in the above script, you will need to make modifications such that the install location matches your desired location. You will also need to specify aws credentials for PSL's private s3 bucket.
-
Load the anaconda3 environment
$ module purge
$ module use -a /contrib/home/builder/UFS-RNR-stack/modules
$ module load anaconda3- Load the Intel 2018 compiler.
$ module load intel/18.0.5.274
$ module load impi/2018.4.274- Point to where the forked version of NCEPLIBS-bufr repo is installed or build
those executables by following the
How to Build and Installinstructions. In other words, add the location of the NCEPLIBS-bufr executables in your PATH environment variable. Examples of these utilities exist here: https://github.com/jack-woollen/NCEPLIBS-bufr/tree/develop/utils
$ export PATH=/contrib/home/builder/nceplibs-bufr/build/utils:$PATHThe observation inventory utilities package primarily is capable of three
functions, search PSL's observation archive, plot each file types file_size
over the date range January 1st 1990 to January 1st 2021, and harvest the
observation counts specified within each file type. The results from the two
different queries are stored in an sqlite database for easy access at a later
time. The results of each command given to determine the file meta of all
observation files related to a given cycle is also stored in a table
cmd_results.
cmd_results
CREATE TABLE cmd_results (
cmd_result_id INTEGER NOT NULL,
command VARCHAR,
arg0 VARCHAR,
raw_output VARCHAR,
raw_error VARCHAR,
error_code VARCHAR,
obs_day DATETIME,
submitted_at DATETIME,
latency VARCHAR,
inserted_at DATETIME,
PRIMARY KEY (cmd_result_id)obs_inventory
CREATE TABLE obs_inventory (
cmd_result_id INTEGER NOT NULL,
obs_id INTEGER NOT NULL,
filename VARCHAR,
parent_dir VARCHAR,
platform VARCHAR,
s3_bucket VARCHAR,
prefix VARCHAR,
cycle_tag VARCHAR,
data_type VARCHAR,
cycle_time INTEGER,
obs_day DATETIME,
data_format VARCHAR,
suffix VARCHAR,
nr_tag BOOLEAN,
file_size INTEGER,
permissions VARCHAR,
last_modified DATETIME,
inserted_at DATETIME,
PRIMARY KEY (obs_id),
FOREIGN KEY(cmd_result_id) REFERENCES cmd_results (cmd_result_id)obs_meta_nceplibs_bufr
CREATE TABLE obs_meta_nceplibs_bufr (
meta_id INTEGER NOT NULL,
obs_id INTEGER NOT NULL,
cmd_result_id INTEGER NOT NULL,
cmd_str VARCHAR,
sat_id INTEGER,
sat_id_name VARCHAR,
obs_count INTEGER,
sat_inst_id INTEGER,
sat_inst_desc VARCHAR,
filename VARCHAR,
file_size INTEGER,
obs_day DATETIME,
inserted_at DATETIME,
PRIMARY KEY (meta_id),
FOREIGN KEY(obs_id) REFERENCES obs_inventory (obs_id),
FOREIGN KEY(cmd_result_id) REFERENCES cmd_results (cmd_result_id)obs_meta_nceplibs_prepbufr
CREATE TABLE obs_meta_nceplibs_prepbufr (
meta_id INTEGER NOT NULL,
obs_id INTEGER NOT NULL,
cmd_result_id INTEGER NOT NULL,
cmd_str VARCHAR,
typ INTEGER,
tot INTETER,
qm0thru3 INTEGER,
qm4thru7 INTEGER,
qm8 INTEGER,
qm9 INTEGER,
qm10 INTEGER,
qm11 INTEGER,
qm12 INTEGER,
qm13 INTEGER,
qm14 INTEGER,
qm15 INTEGER,
cka INTEGER,
ckb INTEGER,
filename VARCHAR,
file_size INTEGER,
obs_day DATETIME,
inserted_at DATETIME,
PRIMARY KEY (meta_id),
FOREIGN KEY(obs_id) REFERENCES obs_inventory (obs_id),
FOREIGN KEY(cmd_result_id) REFERENCES cmd_results (cmd_result_id)obs_meta_nceplibs_prepbufr_aggregate
CREATE TABLE obs_meta_nceplibs_prepbufr (
meta_id INTEGER NOT NULL,
obs_id INTEGER NOT NULL,
cmd_result_id INTEGER NOT NULL,
cmd_str VARCHAR,
typ INTEGER,
tot INTETER,
qm0thru3 INTEGER,
qm4thru7 INTEGER,
qm8 INTEGER,
qm9 INTEGER,
qm10 INTEGER,
qm11 INTEGER,
qm12 INTEGER,
qm13 INTEGER,
qm14 INTEGER,
qm15 INTEGER,
cka INTEGER,
ckb INTEGER,
filename VARCHAR,
file_size INTEGER,
obs_day DATETIME,
inserted_at DATETIME,
PRIMARY KEY (meta_id),
FOREIGN KEY(obs_id) REFERENCES obs_inventory (obs_id),
FOREIGN KEY(cmd_result_id) REFERENCES cmd_results (cmd_result_id)Information regarding the values in the columns for the prepbufr tables can be found from the EMC documentation for typ and quality markers
Example row data from the cmd_results table. Note: an error_code with a negative value indicates that the command failed. The reason for the command failure can be found in the raw_error column.
$ sqlite3 observations_inventory.db
sqlite> select cmd_result_id, command, arg0, error_code, obs_day, latency, submitted_at from cmd_results order by inserted_at desc limit 1;
cmd_result_id command arg0 error_code obs_day latency submitted_at
------------- ---------- --------------------------------------------------------------------------------------------- ---------- -------------------------- ---------- --------------------------
51 sinv /lustre/work/1abffaa1-7ee1-4e8c-9f46-e15d33e04f8f/20150103/gdas.t06z.1bhrs4.tm00.bufr_d/gdas.t06z.1bhrs4.tm00.bufr_d 0 2015-01-03 06:00:00.000000 0.300152 2022-07-05 16:44:07.318004
Example row data from the obs_inventory table.
$ sqlite3 observations_inventory.db
sqlite> select obs_id, filename, platform, s3_bucket, cycle_tag, obs_day, file_size, last_modified, inserted_at from obs_inventory order by inserted_at desc limit 3;
obs_id filename platform s3_bucket cycle_tag obs_day file_size last_modified inserted_at
---------- ------------------------------- ---------- ------------------- -------------- -------------------------- ---------- -------------------------- --------------------------
601 gefsv13_bufr.20150103120000.md5 aws_s3 noaa-reanalyses-pds 20150103120000 2015-01-03 12:00:00.000000 2518 2022-05-25 23:03:12.000000 2022-07-05 16:43:32.124680
600 gdas.t12z.vadwnd.tm00.bufr_d.nr aws_s3 noaa-reanalyses-pds t12z 2015-01-03 12:00:00.000000 378872 2022-05-25 23:03:12.000000 2022-07-05 16:43:32.124638
599 gdas.t12z.updated.status.tm00.b aws_s3 noaa-reanalyses-pds t12z 2015-01-03 12:00:00.000000 10287 2022-05-25 23:03:12.000000 2022-07-05 16:43:32.124602
Example row data from the obs_meta_nceplibs_bufr table.
$ sqlite3 observations_inventory.db
sqlite> select * from obs_meta_nceplibs_bufr order by inserted_at desc limit 5;
meta_id obs_id cmd_result_id cmd_str sat_id sat_id_name obs_count sat_inst_id sat_inst_desc filename file_size obs_day inserted_at
---------- ---------- ------------- ---------- ---------- ----------- ---------- ----------- ------------- ---------------------------- ---------- -------------------------- --------------------------
90 493 51 sinv 223 NOAA 19 179480 607 gdas.t06z.1bhrs4.tm00.bufr_d 29697936 2015-01-03 06:00:00.000000 2022-07-05 16:44:07.750504
89 493 51 sinv 209 NOAA 18 179592 607 gdas.t06z.1bhrs4.tm00.bufr_d 29697936 2015-01-03 06:00:00.000000 2022-07-05 16:44:07.750465
88 493 51 sinv 4 METOP-2 179554 607 gdas.t06z.1bhrs4.tm00.bufr_d 29697936 2015-01-03 06:00:00.000000 2022-07-05 16:44:07.750433
87 493 51 sinv 3 METOP-1 179744 607 gdas.t06z.1bhrs4.tm00.bufr_d 29697936 2015-01-03 06:00:00.000000 2022-07-05 16:44:07.750343
86 492 49 sinv 223 NOAA 19 81000 570 gdas.t06z.1bamua.tm00.bufr_d 13968480 2015-01-03 06:00:00.000000 2022-07-05 16:44:06.777232
The general syntax for executing an inventory search is as follows:
python3 src/obs_inv_utils/obs_inv_cli.py get-obs-inventory -c [search_config_file.yaml]
$ python3 src/obs_inv_utils/obs_inv_cli.py get-obs-inventory -c src/tests/configs/obs_inv_config__valid_s3.yamlExample yaml config file contents:
cycling_interval: 21600
date_range:
datestr: '%Y%m%dT%H%M%SZ'
end: 20150103T180000Z
start: 20150101T000000Z
search_info:
-
platform: aws_s3
key: observations/atmos/gefsv13_reanalysis-md5/%Y%m%d%H%M%S/bufr/
Syntax for the NCEPLIBS-bufr utils sinv command
$ python3 src/obs_inv_utils/obs_inv_cli.py get-obs-count-meta-sinv -c src/tests/configs/obs_meta_sinv__valid_s3.yamlExample yaml config file contents for sinv command to collect observation count file meta.
s3_bucket: noaa-reanalyses-pds
s3_prefix: observations/atmos/gefsv13_reanalysis-md5/%Y%m%d%H%M%S/bufr/
date_range:
datestr: '%Y%m%dT%H%M%SZ'
end: 20150103T060000Z
start: 20150101T000000Z
bufr_files:
- gdas.t%z.1bamua.tm00.bufr_d
- gdas.t%z.1bhrs4.tm00.bufr_d
work_dir: '/lustre/work'
scrub_files: False
Syntax for the NCEPLIBS-bufr cmpbqm command after running the get-obs-inventory command on the necessary files.
$ python3 src/obs_inv_utils/obs_inv_cli.py get-obs-count-meta-cmpbqm -c src/tests/configs/obs_meta_cmpbqm__valid_s3.yamlExample yaml config file contents for cmpbqm command to collect observation count file meta.
s3_bucket: noaa-reanalyses-pds
s3_prefix: observations/reanalysis/conv/prepbufr/%Y/%m/prepbufr/
date_range:
datestr: '%Y%m%dT%H%M%SZ'
start: 20200101T000000Z
end: 20210101T000000Z
prepbufr_files:
- gdas.%z.prepbufr.nr
work_dir: '/lustre/work'
scrub_files: False
Example of syntax used to plot filename file_size over the specified time range.
$ python3 src/obs_inv_utils/obs_inv_cli.py plot_groups_filesize_timeseries -c src/tests/configs/plot_config__data_type_groupings.yamlExample yaml config file for plotting command.
---
plot_groupings:
- grouping_name: Hyperspectral Infrared
data_type_families:
- data_type_family_name: airs
external_obs_intervals:
- obs_src: era5
intervals:
-
start: 10-01-2002
end: 01-01-2030
- obs_src: mera20cr
intervals:
-
start: 10-01-2002
end: 01-01-2030
family_members:
- data_type: airs
suffix: ".tm00.bufr_d"
- data_type: airsev
suffix: ".tm00.bufr_d"
- data_type: airswm
suffix: ".tm00.bufr_d"
- data_type_family_name: cris
external_obs_intervals:
- obs_src: era5
intervals:
-
start: 01-01-2015
end: 01-01-2030
- obs_src: mera20cr
intervals:
-
start: 01-01-2013
end: 01-01-2030
family_members:
- data_type: cris
suffix: ".tm00.bufr_d"
- data_type: crisf4
suffix: ".tm00.bufr_d"
- data_type: crisdb
suffix: ".tm00.bufr_d"
- data_type_family_name: iasi
external_obs_intervals:
- obs_src: era5
intervals:
-
start: 02-01-2007
end: 01-01-2030
- obs_src: mera20cr
intervals:
-
start: 10-01-2008
end: 01-01-2030
family_members:
- data_type: iasidb
suffix: ".tm00.bufr_d"
- data_type: esiasi
suffix: ".tm00.bufr_d"
- data_type: mtiasi
suffix: ".tm00.bufr_d"
Plot created by above yaml.
